文档介绍：致谢
本论文是在导师李伟教授的悉心指导下完成的,他渊博的专业知识、严谨的治
学态度、精益求精的工作作风以及诲人不倦的高尚师德,深深地感染和激励着我。
在此,谨向我的恩师致以深深的敬意。
同时感谢理学院全体老师的热情关心、指导和鼓励,在学****期间同样得到了他
们在学业和生活上所给予的许多帮助,在此深表感谢。
最后,对在我攻读研究生期间的学****生活给予关心、支持和帮助的所有的老
师、同学表示衷心的感谢。
摘要
蚁群算法(Ant Colony Algorithm,ACA)是人们受到自然界中真实蚁群集体行为
研究成果的启发而发展起来的一种新型的模拟进化算法。它具有稳健性(鲁棒性)、
正反馈、分布式计算、易与其它算法结合等优点,具有很好的发展前景。
本文首先对蚁群算法的基本原理进行了介绍,给出了几种改进的蚁群算法,通
过对这些算法作了比较系统的对比与分析。提出一种改进的自适应蚁群算法的一般
模型。除此之外,并针对蚁群个体设计了交叉、变异和选择操作,使得在进化的过
程中可以自适应的调整算法参数,蚁群算法发展演变成了一个全新的模式。将改进
的进化自适应蚁群算法应用于生物遗传领域进行 DNA 序列比对,通过算例仿真表
明算法的有效性;并从理论方面对该算法进行了收敛性证明。实验结果表明,在 DNA
的序列比对中改进的蚁群算法比基本蚁群算法更加有效。
关键词:蚁群算法;自适应蚁群算法;MMAS;基因序列比对
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Abstract
Ant colony algorithm is a novel simulated evolutionary algorithm which is inspired
by the researching result of the imitation of the collective behavior of the biological ant
colony. It shows many promising characters, such as the stability (or robustness),
positive feed-forward, puting, and flexibility bination with other
optimization algorithms. Therefore, it has been developed to one of potential good
optimization tools.
In this paper, we firstly introduce the fundamental principle of the ant colony
algorithm, and discuss some improved ant colony algorithms. A detailed description and
comparison are given in the paper. We developed an improved Adaptive Ant-colony
Algorithm model and designed the evolution operation of crossover, mutation and
selection, in order to adaptively adjust the parameters used in the model. The proposed
Adaptive ant-colony algorithm is applied to the field of bio-ic for DNA sequence
alignment. Some experiments are taken to validate the efficiency of the proposed
method, and the convergence of the proposed algorithm is also given. The results of
DNA gene sequence alignment prove the superiority of the proposed method to the
original algorithm.
Key Words:Ant colony algorithm; adaptive ant colony algorithm; MMAS; gene
sequence alignment
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目录
摘